🎯 Free MLA-C01 Mock Exam

MLA-C01 Mock Exam Questions (Page 1 of 3)

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1. Question #1Domain 1

   A data scientist needs to preprocess a 10-million-row dataset for ML training including feature scaling, categorical encoding, and handling missing values. Which AWS service provides serverless, pay-per-use data preparation for ML at scale?

   AAWS Glue DataBrew

   BAmazon SageMaker Data Wrangler

   CAmazon Athena

   DAWS Lambda
2. Question #2Domain 1

   A team is training a binary classification model for fraud detection. The training dataset contains 98% legitimate and 2% fraudulent transactions. Which technique best addresses this class imbalance?

   ARemove the minority class entirely

   BUse only the minority class for training

   CApply SMOTE or undersample the majority class

   DNormalize all numeric features
3. Question #3Domain 1

   A company builds ML models that use many shared features across different models. They want a centralized, versioned store for these features. Which SageMaker feature should they use?

   ASageMaker Model Registry

   BSageMaker Feature Store

   CSageMaker Experiments

   DSageMaker Pipeline
4. Question #4Domain 1

   A data scientist needs to join features from multiple datasets stored in Amazon S3 for model training within SageMaker without writing custom ETL code. Which SageMaker tool provides a visual, low-code data flow interface?

   ASageMaker Studio

   BSageMaker Processing Jobs

   CSageMaker Data Wrangler

   DSageMaker Ground Truth
5. Question #5Domain 1

   An ML team processes large volumes of labeled training data and wants to outsource the annotation of images to human labelers with quality control. Which SageMaker feature manages this?

   ASageMaker Data Wrangler

   BSageMaker Ground Truth

   CSageMaker Feature Store

   DSageMaker Clarify
6. Question #6Domain 1

   An ML engineer wants to automatically analyze feature importance and identify low-quality features that add noise before training. Which SageMaker feature provides feature importance analysis?

   ASageMaker Feature Store

   BSageMaker Clarify

   CSageMaker Autopilot

   DSageMaker Processing
7. Question #7Domain 2

   An ML engineer is training a deep learning model on a large image dataset. The training job runs for 10+ hours. They want to resume training from a checkpoint if the job is interrupted. Which SageMaker feature enables this?

   ASageMaker Experiments

   BSageMaker Debugger

   CSageMaker Checkpoint Support (model artifacts saved to S3)

   DSageMaker Managed Spot Training
8. Question #8Domain 2

   A team wants to minimize training costs by using unused EC2 capacity for their SageMaker training jobs, accepting occasional interruptions. Which SageMaker feature reduces training costs by up to 90%?

   ASageMaker Multi-Model Endpoints

   BSageMaker Managed Spot Training

   CSageMaker Elastic Inference

   DSageMaker Serverless Inference
9. Question #9Domain 2

   A team runs many training experiments and wants to track hyperparameters, training metrics, and model artifacts across all runs to identify the best model. Which SageMaker service provides this experiment tracking?

   ASageMaker Model Monitor

   BSageMaker Debugger

   CSageMaker Experiments

   DSageMaker Model Registry
10. Question #10Domain 2

    An ML engineer notices that their neural network training loss is not decreasing after epoch 5. They want to visualize the computational graph and identify potential issues like vanishing gradients in real time. Which SageMaker tool provides this?

    ASageMaker Autopilot

    BSageMaker Clarify

    CSageMaker Debugger

    DSageMaker Model Monitor